U.S. patent application number 15/069271 was filed with the patent office on 2016-07-07 for system and method for adaptive active noise reduction.
The applicant listed for this patent is Lightspeed Aviation, Inc.. Invention is credited to Michael J. WURTZ.
Application Number | 20160196819 15/069271 |
Document ID | / |
Family ID | 56286836 |
Filed Date | 2016-07-07 |
United States Patent
Application |
20160196819 |
Kind Code |
A1 |
WURTZ; Michael J. |
July 7, 2016 |
SYSTEM AND METHOD FOR ADAPTIVE ACTIVE NOISE REDUCTION
Abstract
A system and method for adaptive active noise reduction measure
the acoustic response for each user to adaptively adjust and
customize the ANR operation using adaptive filters to correct for
any differences between the measured response and a targeted
response. The system and method of various embodiments incorporate
a closed loop control system with a feedforward input. The acoustic
measurement and adaptation procedure is performed to adapt or tune
at least one of the closed loop and feedforward control loops to
provide adaptive ANR customized for each user and current ambient
environment.
Inventors: |
WURTZ; Michael J.; (Lake
Oswego, OR) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Lightspeed Aviation, Inc. |
Lake Oswego |
OR |
US |
|
|
Family ID: |
56286836 |
Appl. No.: |
15/069271 |
Filed: |
March 14, 2016 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14445048 |
Jul 28, 2014 |
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15069271 |
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61859293 |
Jul 28, 2013 |
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Current U.S.
Class: |
381/94.3 |
Current CPC
Class: |
G10K 11/17861 20180101;
G10K 11/17815 20180101; G10K 11/17817 20180101; H04R 2460/01
20130101; G10K 2210/1081 20130101; G10K 11/17825 20180101; G10K
11/17823 20180101; G10K 11/17881 20180101; H04R 1/1083 20130101;
G10K 11/17857 20180101; G10K 11/17854 20180101; G10K 11/178
20130101; G10K 11/17885 20180101; G10K 2210/3027 20130101; G10K
2210/3055 20130101 |
International
Class: |
G10K 11/178 20060101
G10K011/178; H04R 1/10 20060101 H04R001/10 |
Claims
1. An active noise reduction system, comprising: first and second
earphones; an error sense microphone associated with each of the
first and second earphones; an ambient noise microphone associated
with each of the first and second earphones and coupled to ambient;
first and second drivers associated with the first and second
earphones, respectively; and a controller in communication with the
error sense microphones, the ambient noise microphones, and the
drivers, the controller configured to determine adaptive
coefficients for a feedforward filter independent of a noise
spectrum transfer function in response to at least one transfer
function estimated using at least one of the error sense and
ambient noise microphones, and an associated one of the drivers,
and apply the adaptive coefficients to a feedforward filter between
each ambient noise microphone and the associated driver.
2. The system of claim 1, the controller being further configured
to determine the adaptive coefficients based on a signal provided
to at least one of the drivers, and the transfer function measured
using the error sense microphone and the ambient noise
microphone.
3. The system of claim 2 further comprising a communication
microphone in communication with the controller, the controller
being further configured to determine the adaptive coefficients
only when a signal from the communication microphone is less than
an associated threshold.
4. The system of claim 2, further comprising a memory in
communication with the controller, the controller being further
configured to: store data used to determine the adaptive
coefficients in the memory; and retrieve previously stored data
from the memory in response to power-on of the system to determine
the adaptive coefficients.
5. The system of claim 2 further comprising a memory in
communication with a microprocessor, the controller being further
configured to: store the adaptive coefficients in the memory; and
retrieve previously stored adaptive coefficients from the memory in
response to a system input.
6. The system of claim 1, the controller being further configured
to: apply a stimulus signal to at least one of the drivers, the
stimulus signal having predetermined audio characteristics for use
in determining the adaptive coefficients for the feedforward
filter.
7. The system of claim 6, the controller configured to retrieve
previously stored adaptive coefficients or previously stored data
associated with the adaptive coefficients from a memory for the
feedforward filter rather than applying a stimulus signal to
determine the adaptive coefficients.
8. The system of claim 1, the controller being configured to
receive personalization settings used to determine the adaptive
coefficients from a linked user device.
9. The system of claim 1, the first and second earphones comprising
circumaural earcups each having a driver and error sense microphone
disposed therein, the system further comprising: a first covering
extending within each earcup and covering the driver and the error
sense microphone; and a second covering extending within each
earcup to the error sense microphone, the second covering extending
over only a portion of the driver and not extending over the error
sense microphone.
10. The system of claim 9 wherein the first covering is more
acoustically open than the second covering.
11. The system of claim 9 further comprising: first and second
cushions each extending around a periphery of respective earcups,
the error sense microphone and the driver being positioned within a
respective earcup such that the error sense microphone is closer
than the driver to a plane passing through an associated compressed
cushion periphery.
12. The system of claim 1, the controller being further configured
to: determine a first instance of the adaptive coefficients during
a first time period; determine a second instance of the adaptive
coefficients during a second time period; apply the second instance
of the adaptive coefficients only if a transfer function using the
second instance results in a signal having reduced loudness.
13. The system of claim 1, the controller further configured to:
apply a test signal to at least one of the first and second
drivers; and determine a driver-to-mic transfer function estimate
based on a received signal from at least one of the error sense and
ambient noise microphones in response to the test signal.
14. The system of claim 13 wherein the controller determines an
estimate of the driver-to-mic transfer function based on an impulse
response estimate of the error sense microphone to an impulse
applied to at least one of the drivers.
15. The system of claim 1 further comprising a second microphone
associated with each earphone, the error sense microphone being
positioned closer to an associated driver than the second
microphone, the controller configured to perform closed loop
feedback control based on a signal from the error sense
microphone.
16. The system of claim 15 wherein the first and second earphones
comprise circumaural earcups, the second microphone being
positioned closer to a plane of an open end of an associated ear
cup than the error sense microphone to position the second
microphone closer to an ear opening of a user than the error sense
microphone.
17. The system of claim 1, the controller configured to: determine
the adaptive coefficients based on first and second signal types
associated with the error sense and ambient noise microphones
including a first signal type occurring when a) no signal other
than an anti-noise signal is provided to the drivers and a second
signal type occurring when a test signal is provided to the
drivers, or b) when a communication signal received from an
external input provided to the drivers.
18. The system of claim 17 wherein the first signal type is
associated with ambient noise detected by the ambient noise
microphone and the second signal type is associated with a test
signal applied to the driver.
19. The system of claim 17, the controller configured to apply a
weighting factor to the first signal type to weight contributions
of received signals based on elapsed time from receipt of the
signals.
20. An active noise reduction headset, comprising: first and second
earpieces; first and second sense microphones associated with each
of the first and second earpieces, respectively, directed toward an
ear opening during use; first and second ambient noise microphones
associated with the first and second earpieces, respectively, and
coupled to ambient; first and second drivers coupled to the first
and second earpieces, respectively; and a controller having a
microprocessor, the controller in communication with the first and
second sense microphones, the first and second ambient noise
microphones, and the first and second drivers, the controller
configured to measure a transfer function from ambient noise
detected by one of the ambient noise microphones to at least one of
the sense microphones and, in response, determine adaptive filter
coefficients to generate a driver signal applied to at least one of
the drivers.
21. The headset of claim 20, the controller configured to apply a
test signal to the drivers and determine the adaptive filter
coefficients in response to the test signal.
22. The headset of claim 21 wherein the test signal is applied in
response to a user input.
23. The headset of claim 21 wherein the test signal is applied to
the drivers for use in determining the adaptive filter
coefficients, the controller configured to store adaptive filter
coefficient data in memory and retrieve the adaptive filter
coefficient data in response to subsequent user input for use in
determining the adaptive filter coefficients without subsequent
application of the test signal.
24. The headset of claim 20, the first and second earpieces
comprising circumaural earcups, each earcup having a respective one
of the first and second sense microphones, ambient noise
microphones, and drivers contained therein.
25. The headset of claim 20 further comprising a communication
microphone in communication with the controller.
26. A method for providing active noise reduction (ANR) for a
headset having first and second earpieces, at least one earpiece
including an associated ambient noise microphone, a feedback signal
microphone, and a driver in communication with a
microprocessor-based controller, the method comprising: applying a
test signal to the driver; estimating, by the controller, a first
transfer function associated with the ambient noise microphone and
the feedback signal microphone based on signals received by the
ambient noise microphone and the feedback signal microphone while
the test signal is applied to the driver; estimating, by the
controller, a second transfer function associated with the ambient
noise microphone and the feedback signal microphone based on
signals received by the ambient noise microphone and the feedback
signal microphone with no signal other than an ANR signal applied
to the driver; and determining filter coefficients based on the
first and second transfer functions, the filter coefficients
associated with at least one filter applied to signals received by
the feedback signal microphone and the ambient noise microphone to
generate the ANR signal applied to the driver.
27. The method of claim 26, the test signal being generated by the
controller.
28. The method of claim 26, the test signal comprising an audio
signal generated by an external device.
29. The method of claim 26 further comprising: storing the filter
coefficients or data associated with determining the filter
coefficients in a memory; and retrieving the filter coefficients or
the data associated with determining the filter coefficients from
the memory upon power-up of the headset.
30. A system comprising: first and second earphones associated with
first and second drivers, respectively; first and second ambient
noise microphones associated with the first and second earphones,
respectively; first and second error microphones; and a controller
having a microprocessor, the controller in communication with the
error microphones, the drivers, and the ambient microphones, the
controller configured to: apply an adaptive filter to at least one
signal path between the error microphones, the ambient microphones,
and the drivers, the adaptive filter having coefficients determined
by the controller based on estimates of at least two signal path
input/output relationships, the estimates determined by the
controller based on measurement data sets associated with signals
provided by the error microphones and the ambient microphones that
produce at least two linearly independent equations
Description
CROSS-REFERENCE TO RELATED APPLICATION
[0001] This application is a continuation of U.S. Ser. No.
14/445,048 filed Jul. 28, 2014, which claims the benefit of U.S.
provisional application Ser. No. 61/859,293 filed Jul. 28, 2013,
the disclosures of which are hereby incorporated in their entirety
by reference herein.
TECHNICAL FIELD
[0002] This disclosure relates to a system and method for adaptive
active noise reduction that may be used in various applications
including headphones, headsets, and earphones, for example.
BACKGROUND
[0003] Active noise reduction (ANR) devices have been commercially
available for over 20 years. In general, these devices use
electronics to generate a signal with the same amplitude but
opposite phase of the noise. This is accomplished using a closed
loop feedback control system having a sensing microphone to detect
the noise with the associated signal passed through a compensating
filter and electronics to drive a speaker that produces a pressure
wave out of phase with the noise, resulting in a net reduction or
attenuation of the noise perceived by a user.
[0004] Techniques for designing a feedback control system for
active noise reduction are well understood by those skilled in the
art. In general, the goal may be summarized as selecting components
to provide system operating characteristics that satisfy control
theory feedback loop stability criteria and provide a net
attenuation or reduction of sound pressure at some or all of the
frequencies of interest. This is accomplished by determining an
appropriate open loop gain G, defined as the output/input ratio
when the loop including the driver, sensing microphone, and
electronics is driven and measured with the loop open, i.e. without
feedback. G is a complex function, such that its magnitude and
phase vary with frequency.
[0005] The corresponding attenuation provided by a system with open
loop gain G can be expressed as 1/(1-G). In closed loop ANR
circumaural designs having ear cups with a cushion that seals
against the head around the circumference of the ear, this is
typically limited to frequencies under 1 kHz. Because of a need for
more attenuation of the lower frequencies, some boosting or
amplification of the sound pressures is tolerated at higher
frequencies where passive attenuation is more effective. In closed
loop control systems, the amount of attenuation at lower
frequencies is dependent on the acceptable phase margin around the
upper transition frequency where the magnitude of the open loop
gain (IGI) reaches unity. Phase margin is defined as the phase
difference between the phase angle of the open loop gain (<G)
and zero degrees when IGI=1. If the open loop gain has a magnitude
close to unity and a phase of close to zero degrees, the
denominator of 1/(1-G) will be much less than unity resulting in
the function 1/(1-G) being much greater than unity at those
frequencies and thus boosting of the pressure around those
frequencies. Any compensation that causes a net decrease in
amplitude with increasing frequency, has a resultant negative phase
shift with more phase shift associated with steeper
attenuation.
[0006] If 60 degrees or more phase margins can be maintained when
the magnitude of the open loop gain (IGI) is close to unity, then
no high frequency boosting will exist. Unfortunately, this
generally produces inadequate loop gain at lower frequencies where
passive attenuation is not as significant. Many designs accept some
amount of high frequency boosting (making some frequencies louder
when the ANR is on or active) to gain more attenuation at lower
frequencies. In the design of such a system, transport or transit
delay between the microphone input and driver output uses up
valuable phase margin, and without changing the compensation,
increases boosting around frequencies where the magnitude of G
(IGI) is approximately unity. As a result, the sensing microphone
has been placed in close proximity to the speaker (driver) to
minimize delay as a result of the travel time of the sound to reach
the microphone to provide acceptable phase margin and increase
system bandwidth. In addition, the assumption of constant pressure
within the front cavity of the ear cup of circumaural headphones at
the frequencies the system attenuates also supports this approach
as a good design methodology.
[0007] As such, use of well understood principles of feedback
control system design and accepted operating assumptions have
resulted in prior art systems that position the sensing microphone
close to the speaker (also referred to as the driver) to maximize
system bandwidth while providing acceptable phase margin for the
system to remain stable and avoid unacceptable boosting of higher
frequencies. The system parameters to provide acceptable phase
margin are generally determined during product development based on
average anatomical data and representative use scenarios. These
parameters are generally fixed for the life of the product, or in
some cases may be infrequently changed during firmware updates, but
do not change during each use. While suitable for many
applications, this design methodology does not account for
variations among users with respect to ear anatomy as well as
ambient environment.
[0008] Microprocessors and various dedicated purpose digital
devices have afforded the opportunity for more complex digital
processing of audio signals. However, processing speed remains an
important consideration for real-time applications as any
significant delay (on the order of 10 milliseconds) may produce an
unacceptable lag, echo, distortion, or similar effect leading to an
unnatural listening experience that may also affect speech
patterns. Delay also imposes an inherent limitation to the
bandwidth of broadband cancellation. The desire to avoid these
effects may result in limiting the ANR performance over certain
frequency bands.
SUMMARY
[0009] A system and method for adaptive active noise reduction
according to embodiments of the present disclosure measure the
acoustic response for each user to adaptively adjust and customize
the ANR operation using adaptive filters to correct for any
differences between the measured response and a target response.
The system and method of various embodiments incorporate a closed
loop control system with a feedforward input. The acoustic
measurement and adaptation procedure is performed to adapt or tune
at least one of the closed loop and feedforward control loops to
provide adaptive ANR customized for each user and current ambient
environment.
[0010] During an initialization or calibration mode, the
feedforward control is adapted to the user and ambient environment
by measuring the transfer function from the ambient noise to the
sense or error microphone positioned within the earcup of the
headset. This information is used to implement a corresponding
filter having the opposite phase to provide noise reduction or
cancelation. To produce an accurate anti-noise signal that matches
the acoustic noise in the ear cup using the ambient microphone as
the sense microphone, the transfer function of the driver to error
microphone must also be known. With the transfer functions of the
ambient microphone to error microphone and the driver to error
microphone known, it is possible to estimate the required target
transfer function to produce perfect cancelation. This target
transfer function can then be used to compute a realizable filter.
This method differs from the typical approach used with adaptive
filters that modifies coefficients to minimize the error energy
using any of a number of strategies that may be characterized as
gradient descent strategies. In contrast, using a method based on
target transfer functions according to embodiments of the present
disclosure is fundamentally different in that it is independent of
the spectrum of the noise source, i.e. the amount of energy at a
given frequency does not affect the target response, or the
resulting realizable transfer function. As a further benefit, the
problem with convergence of gradient descent methods with wide
eigenvalue disparity (i.e. natural frequencies of the transfer
function that span a large range of frequency, say 10's of Hz to
several kHz) is avoided.
[0011] To facilitate substantial contribution from the feedforward
input, the sense or error microphone is positioned within at least
one earcup to be in very close proximity to the ear canal opening
of the user when the headset is worn (as close as practically
possible considering variations in anatomy without contacting the
user). This minimizes the difference between the error microphone
and the sound at the ear canal to provide a more accurate
measurement of the sound or noise heard by the user.
[0012] Positioning the error microphone as described above causes
an additional complication in that the differences between each
user and even each use/fit are very sensitive to the pinna
reflections and ear canal resonance, which would make a traditional
fixed filter type of implementation very difficult or cause reduced
performance to accommodate different users. Embodiments according
to the present disclosure address this problem by adapting or
customizing the loop response to each individual. As a result,
closed loop performance is improved and, more significantly,
feedforward cancelation is substantially improved relative to
various prior art ANR devices. A similar method is used in the
feedforward cancelation of various disclosed embodiments where the
noise transmission transfer function is estimated, and a
synthesized transfer function is implemented to provide an
anti-noise signal from the driver/speaker. This feature may operate
separately, or in combination with the closed loop ANR
function.
[0013] Embodiments according to the present disclosure may
continually monitor ANR operation and selectively update or adapt
one or more system variables or parameters, such as the
driver-to-microphone transfer function T.sub.dm and the
noise-to-error-sensing-microphone transfer function T.sub.nm for
example. System performance can be continually monitored and
filters for closed loop and feedforward noise reduction updated
during operation as desired to improve noise cancellation. T.sub.dm
can use communication signals as the stimulus to update the
estimate of T.sub.dm using a moving average. This method is also
useful for correcting variations over time, such as altitude
changes for aviation applications and changes in the ear seal
caused by perspiration. T.sub.nm is technically not noise
dependent, but the amplitude and phase vs frequency weighting used
to estimate the feedforward filters may incorporate a factor that
focuses the accuracy of the feedforward transfer function T.sub.ff
(H.sub.ff). Using a weighting that approximates perceived loudness
aids in insuring that future updates to these parameters are
perceived by the user as improving performance and not just
mathematically better based on a lower weighted calculated energy,
where the weighting is an approximation of the psycho-acoustic
weighting to perceived loudness.
[0014] After system characterization, a user can save his
personalized response to allow for immediate loading of the
personalized response during subsequent use. The saved filters
and/or other parameters can be updated during operation to
accommodate variations in a particular fit or operating
environment.
[0015] In addition to using communication signals to adapt one or
more system parameters, various embodiments provide customized
characterization for a user and/or application using an active
stimulus signal, which may more quickly provide the
characterization parameters by using a known stimulus signal having
desired frequency, amplitude, and phase characteristics.
Characterization using an active stimulus may not provide optimal
ANR performance for each fit, but will typically be sufficient for
good performance, and can adapt (or update the T.sub.nam and
T.sub.dm estimate) by using passive estimates (i.e. using a
communications signal for the stimulus and other data when the comm
signal is not present to provide data for T.sub.nam during
subsequent operation).
[0016] In various embodiments, T.sub.nam estimates can also be
updated periodically, and used to monitor performance. If T.sub.nam
changes significantly, the feedforward filters T.sub.ff can be
updated from this data. Filters are only updated if the estimated
perceived performance is improved. This is done by weighting the
estimated change in noise level at the error sensing microphone by
the appropriate weighting filter and the spectrum of the noise at
the error sensing microphone.
[0017] In some embodiments, performance is further improved by the
use of two microphones in the ear cavity of the earcups. The second
ear cup microphone for error sensing of the closed loop system is
optimally positioned to trade off delay from the driver to the
closed loop error microphone while providing only enough
correlation to the ear to support the closed loop attenuation. This
can allow the closed loop attenuation to extend to a higher
frequency. The first error sensing microphone is again positioned
very close to the ear canal opening, or for applications that will
tolerate it, even in the ear cavity opening. In this case, the ear
canal error sensing microphone need not be processed as a low
latency signal, since it is only used for estimating the pressure
at the ear opening.
[0018] In other embodiments, the error signal is modified to
account for the differences between T.sub.dm, T.sub.de, T.sub.nm,
and T.sub.ne. The goal of the adaptive filter algorithm is then to
force the response of the error sensing microphone to a
pre-determined function of frequency which reduces or minimizes the
noise at the ear drum, as opposed to the adaptive filter attempting
to minimize the weighted error.
[0019] Various embodiments of an adaptive ANR system or method
according to the present disclosure provide associated advantages.
For example, typically, ANR headsets only perturb the pinna
response slightly, and as with any headphone, the response is
influenced by the user's own anatomy, particularly the pinna. The
best performing headphones are usually circumaural types that are
very leaky, so as to minimize corruption of the users unique pinna
response. Embodiments according to the present disclosure
significantly reduce or entirely remove any effect of the pinna on
sound going into the ear (typically, variations from 2 kHz-20 kHz).
By processing the calibration data done on a flat plate or block
head with no pinna, and the user's calibration based on an active
stimulus or a communication signal, the user's pinna response can
be measured and restored. In addition to circumaural headphones,
the measured pinna response is valuable for restoring the pinna
response to ear bud or in-the-ear type headphones. The restoration
of the pinna response as an equalization applied to incoming music
signals provides a dramatic improvement over traditional headphone
experiences because it is not the result of the pinna and headphone
response, but primarily just the pinna response, thus producing an
audio response that is very natural, and simultaneously providing
very good isolation.
[0020] Various embodiments according to the present disclosure
allow the noise reduction system to come on in a conservative
manner that will be stable for all users, and then measure the key
variables, such as T.sub.nm and T.sub.dm, for example, using one or
more measurement strategies. When audio is being played to the
user, estimates of T.sub.dm can be calculated. Use of time
averaging of the frequency spectra with a weighting that updates
the parts of the T.sub.dm(f) that have good excitation greatly
improves the speed and accuracy. For example, if very low frequency
content or very high frequency content was not present, only the
part of the response that was adequately excited is used to improve
the estimate of T.sub.dm(f). T.sub.nm can be estimated ideally
without audio. The boom microphone signal provided by headset
embodiments can be used to detect if the user is talking, and if
this is the case, then the ambient noise is correlated to the
communication audio if loop back is present. Also, user speech
causes bone conduction that will not be present at the ambient
microphone(s), thus it is better to avoid use of measurements when
the user is talking. Corrections can be made for communications
audio signals if the transfer function is known.
[0021] As previously described, various embodiments allow user
initiated saving of characterization or calibration data within the
headset, or the headset can save the adapted filter coefficients
before power down. Alternatively, or in combination, calibration
data and/or filter coefficients may be saved and restored from a
linked device, such as a cell phone.
[0022] In addition to circumaural headphones, various features of
the embodiments according to the present disclosure may be used in
supra-aural and intra-aural (or in-the-ear) type of headphones.
[0023] The above advantages and other advantages and features will
be readily apparent to those of ordinary skill in the art based on
the following detailed description when read in combination with
the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0024] FIGS. 1A-1C illustrate a representative circumaural
implementation of a system or method for adaptive ANR according to
embodiments of the present disclosure;
[0025] FIG. 2 illustrates a prototype circumaural headset having
adaptive ANR according to embodiments of the present
disclosure;
[0026] FIG. 3 is a simplified control system block diagram and
supporting equations used to determine various transfer functions
associated with an adaptive ANR system or method according to
embodiments of the present disclosure;
[0027] FIG. 4 is a conceptual block diagram illustrating various
functional blocks for adaptive ANR including sense microphones,
drivers, and external inputs according to embodiments of the
present disclosure;
[0028] FIG. 5 is a block diagram illustrating sample-by-sample
(SBS) low latency processing and adaptive filter coefficient
calculator for adaptive ANR according to embodiments of the present
disclosure;
[0029] FIG. 6 is a block diagram illustrating system architecture
for a representative embodiment of an adaptive ANR headset
according to the present disclosure;
[0030] FIGS. 7A (Prior Art) and 7B illustrate improved low latency
audio processing for adaptive ANR according to representative
embodiments of the present disclosure;
[0031] FIG. 8 is a block diagram illustrating integration and
configurability details provided by a linked device or other user
interface for an adaptive ANR system or method according to various
embodiments of the present disclosure;
[0032] FIGS. 9-19 are graphs illustrating improved ANR performance
for an adaptive ANR system or method according to embodiments of
the present disclosure.
DETAILED DESCRIPTION
[0033] As required, detailed embodiments of the present invention
are disclosed herein; however, it is to be understood that the
disclosed embodiments are merely exemplary of the invention that
may be embodied in various and alternative forms. The figures are
not necessarily to scale; some features may be exaggerated or
minimized to show details of particular components. Therefore,
specific structural and functional details disclosed herein are not
to be interpreted as limiting, but merely as a representative basis
for teaching one skilled in the art to variously employ the present
invention.
[0034] In general, the system and method operate by providing
customized or adaptive ANR that adapts to each individual user and
environment. The basic concept is that the system and method
calibrate or adapt the closed loop system to the user and/or fit
that reflects the current position of the headset on the user.
Compared to traditional methods, this minimizes the effect of
unit-to-unit variations caused by manufacturing, user variables,
such as pinna shape and size, leak variations due to more or less
hair, etc. Additionally, even for the same users, from fit to fit,
and over time, variations occur that are caused by hair and
perspiration and slight position variations relative to the sensing
microphone and the ear opening. As described in greater detail
herein, embodiments according to the present disclosure
periodically and/or continuously adapt the system parameters to
improve the overall ANR performance over varying user fit and
ambient conditions to provide a customized ANR experience.
[0035] FIGS. 1A-1C illustrate a representative circumaural
implementation of a system or method for adaptive ANR according to
embodiments of the present disclosure. While the representative
embodiment is depicted as a circumaural headset with a boom
microphone, those of ordinary skill in the art will recognize that
strategies of various embodiments may also be used to advantage in
other types of headphones, earphones, etc, such as in-the-ear (ITE)
and on-the ear (or supra-aural) implementations. FIG. 1A is a
diagram representing a cross section of one embodiment illustrating
positioning of various system components. ANR headset 20 includes a
pair of similarly equipped ear cups 22, only one of which is shown,
connected by a band (FIG. 2). Ear cup 22 is used to support a
cushion 24 that fits over and surrounds the pinna of the ear of a
user during use. Cushion 24 is partially compressed to provide a
seal around the ear. Ear cup 22 supports a driver or speaker 26 as
well as an ANR or error microphone 28. Acoustically "open" cloth or
foam 30 covers driver 26 and error microphone 28. A second layer 32
of foam or cloth that is more acoustically dense may be provided to
cover at least a portion of the driver 26, but does not cover error
microphone 28 in this embodiment. Second layer 32 may also be
implemented as a portion of cloth or foam 32. Ear cup 22 may
include one or more vents that may be covered by a cover plate 34
and damping material such as foam 36.
[0036] FIGS. 1B and 1C illustrate an alternative embodiment that is
similar to the embodiment of FIG. 1A, but includes a second ANR or
error microphone to detect ambient noise. As illustrated in the
inside view of FIG. 1B and cross-section of FIG. 1C, system 40
includes an ear cup 42 having a cushion 44 that partially
compresses against the head 70 of a user during operation. The
pinna 72 and tragus 74 of the user's ear extends within the portion
of ear cup 42 in front of acoustic fabric 50. Driver or speaker 46
is positioned within ear cup 42 generally behind sense microphone
48, which is positioned near the opening of ear canal 76 and tragus
74 of user 70. An optional second sense or error microphone 60 is
used to detect ambient noise and provide a corresponding signal to
the ANR processing circuitry to improve performance based on
current operating conditions. In this embodiment, ambient noise
microphone 60 is positioned behind a corresponding opening in ear
cup 42 and covered by a rigid cover plate 54 and layer of foam 56
or similar material. Ear cup 42 may also include a vent 62 sized to
provide desired response of driver 46.
[0037] As illustrated in FIGS. 1B-1C, the sense microphone 48 is as
close to the tragus 74 of the user 70 as possible. (i.e. over the
population, any closer may start to cause comfort issues). The path
distance (string length) from the driver 46 to the microphone 48 is
greater than the string length from the microphone 48 to the tragus
74 of user 70. Closeness to the ear opening is believed to be more
important than distance from the driver 46 in this embodiment. This
would be very problematic in a conventional system that does not
adapt to variation associated with fit and anatomy as different
shapes and sizes of pinnas can otherwise cause significant
variation in the 1 kHz-3 kHz regions that adversely affect closed
loop stability.
[0038] The close proximity of the sense microphone 48 to the ear
opening 76 allows the microphone to match the ear so that
cancelation can be up to 20 dB out to 2 kHz and much more at lower
frequencies as generally demonstrated by the graphs of FIGS.
9-19.
[0039] FIG. 2 illustrates a prototype circumaural headset having
adaptive ANR according to embodiments of the present disclosure.
The perspective view of FIG. 2 illustrates a headset 40 having ear
cups 42 connected by a head band 80. A boom microphone 82 extends
from one of the ear cups 42 and is used to capture user speech.
Headset may be coupled to a signal source by a corresponding cord
or cable 84, or may be wireless connected in some
implementations.
[0040] FIG. 3 is a simplified control system block diagram and
supporting equations used to determine various transfer functions
associated with an adaptive ANR system or method and to illustrate
operation of a system or method for adaptive ANR according to
embodiments of the present disclosure. The control system block
diagram of FIG. 3 may be used to derive a target feed forward
response (H.sub.B) that would provide total noise cancellation in
an idealized system. The block diagram of FIG. 3 includes an input
for a signal from an ambient noise microphone, although those of
ordinary skill in the art will recognize that the same principles
may be applied to systems that do not include an ambient noise
microphone or associated signal.
[0041] In contrast to prior art ANR strategies, embodiments of the
present disclosure estimate transfer functions to do the noise
cancelation. Previous strategies rely on methods that depend on the
statistics of the noise. i.e. they cancel the periodic components
of the noise. In the method and system according to the present
disclosure, an adaptive realizable filter is used, specifically, an
IIR filter rather than a FIR filter, with the end result that the
performance measured as attenuation vs frequency is totally
independent of the statistics of the noise. (i.e. periodic methods
don't work well if the noise is not periodic.)
[0042] As shown in FIG. 3, the sense microphone signal M 302 is
multiplied by a linear factor K.sub.1 at 304 and combined at block
306 with the communication (comm) signal 308. The combined signal
is processed by the target response H.sub.A at block 310 and
combined at block 312 with the processed signal associated with the
noise signal N represented at 320. Noise signal N is multiplied by
a constant K.sub.2 as indicated at 322 and the target feed forward
response H.sub.B at block 324 before being combined as described
above at block 312. Noise signal N at 320 is multiplied by Tp at
block 326 with the result provided to block 334. The output of
block 312 is multiplied by e H.sub.C at 330 and T.sub.dm at 332
before being combined at 334 with the output from block 326 to
generate output M at 336, which represents the error or sense
microphone signal used in the feedback loop. Block 332 represents
the response or transfer function between the driver D at 340 and
the sense microphone M at 336.
[0043] Those of ordinary skill in the art will recognize that
measuring the driver to error or sense microphone response between
the driver/speaker 46 and sense microphone 48 represented by
T.sub.dm in use is ideal, and can be done actively or passively.
For active measurement of T.sub.dm according to various embodiments
of the present disclosure, a test signal is used as the stimulus.
This can be any signal that excites the modes of the system. For
example, a multitone, chirp, log chirp, or random noise are some
examples of a possible test signal or active stimulus. A test
signal that is periodic about a value n, where n represents the FFT
size eliminates the need for a window function. Of course, an FFT
is just one basis and the representative methods illustrated will
work independently of the basis chosen for solving the problem.
Other adaptive strategies that minimize the error by a gradient
search may also be used, such as a least mean squares (LMS) or root
mean squares (RMS) optimization, for example.
[0044] The response or transfer function T.sub.dm of block 332 can
also be measured passively, but using normally occurring signals
such as the speech or aircraft noise. If only aircraft noise is
used, the system closed loop response can be perturbed to allow the
simultaneous estimation of both T.sub.dm and T.sub.p. Otherwise,
there is only one equation and two unknowns. To provide a solution,
for the two unknowns requires another equation, i.e. the system is
perturbed (the loop gain of the closed loop filters is changed
slightly so that two equations are created. During the process the
system performance is perturbed for the purpose of determining the
two parameters related to the driver to mic response (T.sub.dm) and
the noise to mic response (T.sub.p) unknowns.
[0045] The following control equations may be derived from the
block diagram illustrated in FIG. 3:
M N = T p + K 2 H B H C T DM 1 - K 1 H A H C T DM + H AH C T DM 1 -
K 1 H A H C T DM comm N ( 1 ) min M - H A H C T DM 1 - K 1 H A H C
T DM comm + .di-elect cons. N 2 ( 2 ) .thrfore. min T p + K 2 H B H
c T DM 2 ( 3 ) .delta. T p + K 2 H B H c T DM 2 .delta. H B = 0 ( 4
) T p + K 2 H B H C T DM = 0 ( 5 ) H B = - 1 K 2 T p / H C T DM ( 6
) D T DM + N T p = M T p = ( M - DT DM ) N ( 7 ) H B = - 1 K 2 ( M
- DT DM ) / N H C T DM ( 8 ) = - 1 K 2 ( T nam H C T DM - T nDm H C
) ( 9 ) T nam = M N * N N * ( 10 ) T nDm = D N * N N * ( 11 )
##EQU00001##
Where the following variable definitions are used in the
representative embodiment illustrated in the Figures and
mathematically represented above:
[0046] M represents the sense/error microphone;
[0047] N represents the ambient noise measured by the ambient
microphone (60, FIG. 1C);
[0048] T.sub.p represents passive attenuation corresponding to M/N
with no active or comm signal present;
[0049] T.sub.nam represents active attenuation at the sense
microphone corresponding to measured M/N with no comm signal
present; and
[0050] T.sub.dm represents the driver to error mic response.
[0051] The system design allows for the sense/error microphone 48
to be placed much closer to the ear opening than previous
implementations. This has the key advantage of being a more
accurate estimate of what the user actually hears. i.e. there will
be smaller differences in T.sub.dm and T.sub.de, and in T.sub.nm
and T.sub.ne.
[0052] The system uses a feedforward method that includes a
feedback loop. For closed loop feedback operation, the signal from
the error microphone M is fed back into the system to reduce noise
as generally represented in FIG. 3 with output 336 and input 302.
In the feedforward mode, the error microphone, which is positioned
as close as possible to the ear opening and much closer than in
conventional ANR applications, more accurately represents audio
heard by the user. This signal is used to monitor performance and
continuously update the transfer function of the feedforward filter
H.sub.B as shown in the block diagrams illustrated and described in
greater detail herein.
[0053] FIG. 4 is a conceptual block diagram illustrating various
functional blocks for adaptive ANR including sense microphones,
drivers, and external inputs according to embodiments of the
present disclosure. The block diagram of FIG. 4 provides a more
detailed representation of the adaptive ANR strategy generally
illustrated in the block diagram of FIG. 3. System 400 provides the
sense or error microphone signal 402 as feedback, which is
multiplied by a constant K.sub.1 at block 404 with the output
provided to preamp and anti-aliasing filter 406. A low latency
analog-to-digital (ADC) converter 408 processes the signal to
provide error data to adaptive feedback filter H.sub.C at 410. As
used in this application, and as described in greater detail below,
a low latency ADC (or DAC) generally refers to a successive
approximation converter with successive approximation registers
that has virtually no delay and that does not include sigma-delta
converters that use linear filters. Oversampling, or sigma-delta
type converters, are not necessarily inappropriate for this type of
low latency application, but both ADC's and DAC's of this type
require a filter to average and provide the required resolution,
which is typically done with a low pass filter/decimation filter.
While these converters are typically linear phase converters that
minimize phase distortion, this is accomplished at the expense of
latency and provides less than desirable results in an adaptive ANR
application such as disclosed herein.
[0054] Adaptive feedback filter 410 is an IIR (infinite impulse
response) filter that is equivalent to a combination of the HA
filter or target response 310 and HC filter 330 illustrated in FIG.
3. The coefficients of adaptive feedback filter 410 may be provided
by adaptation algorithm generally represented by block 450.
Alternatively, filter 410 may use predetermined coefficients
determined during product development rather than adaptive
coefficients determined in response to current operating
environment and user fit. The output of filter 410 is then combined
at 412 with the processed ambient noise signal and digital and
audio noise signals.
[0055] An ambient noise signal 414 is multiplied by an associated
constant K.sub.2 at block 416. Ambient noise signal 414 may be
generated by a corresponding ambient noise microphone, such as
microphone 60 (FIG. 1C). The result is provided to preamp and
anti-aliasing filter 418 with the output of block 418 provided to a
low latency ADC 420 to provide ambient noise data to adaptive feed
forward filter H.sub.FF 422. Adaptive filter 422 has one or more
filter coefficients adaptively determined by an associated
adaptation algorithm 450. Adaptive filter 422 includes aspects of
both an IIR and FIR filter as it is a function of filters or target
responses H.sub.A 310, H.sub.B 324, H.sub.C 330, and TDM 332 as
illustrated and described with reference to FIG. 3. The output of
adaptive filter 422 is then combined at 412 with the outputs of
adaptive feedback filter 410 and adaptive filter 442.
[0056] Analog audio input 430, such as input from a boom microphone
or an external analog audio device coupled to the headset is
provided to preamp and anti-aliasing filter 432 with the output of
filter 432 provided to ADC 434. As illustrated, while a low latency
ADC is suitable, it is not needed to provide desired system
performance for processing of the analog audio input 430. The
output of ADC 434 is combined at 436 with external digital audio
input 438 after processing by SRC at 440, which provides stereo
cross-feed to more accurately represent stereo signals. The
combined signal/data is provided to adaptive filter (CommEQ) at
442, with filter coefficients determined by adaptation algorithm
450. Adaptive filter 442 combines features of an IIR and FIR
filter.
[0057] The combined signal from block 412 is provided to
digital-to-analog converter (DAC) 444. The output of DAC 444 is
then provided to block 446, representing the response T.sub.DM from
the driver to the error/sense microphone, with the output
representing the error signal 402.
[0058] As described above, an adaption algorithm 450 provides
coefficients to adaptive filters 410, 422, and 442 as generally
represented at 460, 462, and 464, respectively. Adaptation
algorithm 450 may be implemented in software and/or hardware. In
the representative embodiments illustrated, adaptation algorithm
450 is implemented by software using a programmed microprocessor
that receives data error input from ADC 408, ambient data input
from ADC 420 and external audio input data from ADC 434 and SRC
440. Adaptation algorithm 450 may also receive ambient input from
an optional ADC 470 used only during the adaptation process. The
input data is used to generate filter coefficients for filter 410
and 422 for enhanced stability and noise attenuation.
[0059] Various embodiments according to the present disclosure
automatically determine the adaptive filter coefficients in
response to current operating conditions. According to these
embodiments, the adaptation algorithm calculates filter
coefficients using only two categories of data corresponding to
data representing audio signals without an active stimulus and
communication signal from the system panel, and data representing
audio signals with either active stimulus or communication from the
system panel (or other external source generating audio signals
through the driver). In one embodiment, the system uses data
generated in response to the active stimulus, and data generated in
response to ambient noise with no active stimulus and no external
audio signal present for the driver.
[0060] Because the system estimates both T.sub.DM and either
T.sub.P (or alternatively T.sub.nam) across the desired frequency
range, there are two unknowns at each frequency. T.sub.DM for
example can be estimated very well if no noise is present, or if
T.sub.nam is known. Alternatively, T.sub.nam can be estimated if
T.sub.DM is known. This is basically solving for two unknowns (at
each frequency) with two equations. However, if the data represents
two samples at different times, differing only by random
measurement errors, but nothing is substantially different, the
system cannot solve for two unknowns. As such, the system uses the
calibration data (active stimulus) for one equation, and a moving
average of subsequent data representing ambient noise without an
external audio signal from the panel or a connected device to
provide the second equation. A best fit strategy or technique is
then used with equal weighting for each data type. Alternatively,
the best fit strategy can use unequal weighting, but should be
controlled so that it does not minimize the data generated in
response to the active stimulus.
[0061] As recognized by the present inventor, it is possible to
estimate the responses using data generated while the user is
speaking. However, this data may not provide the desired results
because it is affected by bone conduction and the ambient estimate
will be biased toward a noise source of the user talking. If the
system excludes this operating condition, then it can obtain the
necessary equations from data generated with an external
communication signal (comm data) present, and no external
communication signal present, to estimate the feedforward transfer
function, which is based on T.sub.DM and T.sub.nam. As such, in one
representative embodiment, the system detects a signal from the
boom microphone indicative of user generated audio signals and
avoids using data generated during these events in the adaptation
algorithm to adjust or adapt the coefficients of the feedforward
filter. Likewise, the system detects an external audio signal, such
as a comm signal from a panel input or another coupled device, and
the adaptation algorithm does not use data generated during these
events to adjust or adapt the coefficients of the feedforward
filter.
[0062] In contrast to prior art ANR strategies, embodiments of the
present disclosure estimate transfer functions to perform noise
cancelation. Previous strategies rely on methods that depend on the
statistics of the noise, i.e. canceling the periodic components of
the noise. In the method and system according to the present
disclosure, an adaptive realizable filter is used, which
incorporates an IIR filter specifically, rather than relying solely
on a FIR filter, with the end result that the performance measured
as attenuation over a range of frequencies is independent of the
statistics of the noise. (i.e. periodic methods don't work well if
the noise is not periodic.)
[0063] As described in greater detail herein, data measurement is
performed by block 450 as needed to provide data for adapting
filters. In addition, stereo cross-feed processing may be performed
here to enhance audio performance. Measurement data from the
sensors and audio inputs may be used to estimate transfer functions
that have the unknowns T.sub.DM and T.sub.NM as generally
illustrated and described with reference to FIG. 3. These estimates
are then used to generate filters having associated coefficients
that compensate for the transfer functions. T.sub.DM and the
variations caused by individual user's pinnas can be compensated
for to enhance the closed loop performance and/or to estimate the
feedforward transfer function T.sub.FF along with the noise
attenuation transfer function T.sub.NM. The net total attenuation
is a function of all system parameters and H.sub.B or H.sub.FF is
then solved in terms of the estimated parameters and known
parameters such as the digital filters for closed loop
functioning.
[0064] FIG. 5 is a block diagram illustrating sample-by-sample
(SBS) low latency processing and an adaptation algorithm strategy
for use in adaptive filter coefficient calculations for adaptive
ANR according to embodiments of the present disclosure. FIG. 6 is a
block diagram illustrating system architecture for a representative
embodiment of an adaptive ANR headset according to the present
disclosure. FIGS. 7A (prior art) and 7B illustrate representative
low latency audio processing for adaptive ANR according to
representative embodiments of the present disclosure. An ANR
headset according to embodiments of the present disclosure
incorporates successive approximation register (SAR) converters and
low latency DAC's as previously described and illustrated to
provide desired system performance. In addition, the system
processes the sampled data using a unique low latency strategy in
contrast to conventional digital data processing techniques.
[0065] FIGS. 7A and 7B provide timing diagrams illustrating
processing of sampled signals acquired during particular sample
time periods for sequentially sampled channels. A representative
prior art digital audio processing strategy is illustrated in FIG.
7A. Sequential sampling periods are represented at 710 with
multiplexed ADC input channels L1-L5 represented at 720. In the
representative embodiment illustrated, five (5) channels are
sampled with L1 having ANR/error microphone data, L2 having ambient
microphone data, L3 having comm channel data, L4 having auxiliary
input channel data, and L5 having boom microphone data. The
processing task timing of the digital signal processor (DSP) is
represented at 730 and the DAC output is represented at 740. Arrow
750 generally represents the lowest possible latency for a signal
on any of the multiplexed inputs to propagate to the DAC (or power
amplifier and associated driver/speaker). The sampling rate in this
example is 170 ksps in this case. Arrow 750 represents the latency
corresponding to two sample periods plus whatever propagation time
is required for the DAC to load. In many audio DSP systems, the DAC
is actually loaded at the end of the third sample period.
[0066] FIG. 7B illustrates an improved low latency processing
strategy incorporated into various embodiments of the present
disclosure. In FIG. 7B, the ADC samples represented at 722 are
acquired during a first sample period represented at 712 and are
used to calculate the filter coefficients for H.sub.A, H.sub.B,
H.sub.C as represented at 732 and output to the DAC as represented
at 742 (or 760 for an ideal DAC). The resulting latency of this
strategy corresponds to one sample period as represented by arrow
752 for an ideal DAC as represented at 760, and slightly longer
than one sample period accounting for group delays, which include
loading delays of a representative DAC as represented at 742.
[0067] As such, the representative prior art digital signal
processing technique illustrated in FIG. 7A, samples data during
sample period (n), processes previously sampled data from sample
period (n-1), and outputs previously processed data from sample
period (n-2), requiring approximately 2.2 sample periods or about
12.8 microseconds accounting for loading of the DAC. In contrast,
as generally illustrated in FIGS. 5, 6, and 7B, embodiments
according to the present disclosure sample data during sample
period (n), and process and output the data (for sample period n)
during the same sample period (n) to reduce latency to
approximately one sample period in this example, or just over one
sample period when accounting for loading delay of the DAC. Stated
differently, the data from one or both of the ANR or sense
microphones is sampled, filtered, and output to the DAC before the
next sample period. As such, for low latency as used herein, the
system latency should be such that the DAC output can be influenced
by ADC inputs in less than 2 sample periods.
[0068] As illustrated in the representative embodiment of FIG. 7B,
data processing does not begin at 734 (misc. data handling) and 736
(computations for H.sub.A, H.sub.B, and H.sub.C) until all five (5)
channels are sampled. In another embodiment, latency is further
reduced by starting processing of one channel before all the
channels have been sampled. For example, processing may start on
the channel carrying ANR sense microphone data for calculation of
the coefficients of H.sub.A as soon as the data is ready. This
introduces aliasing and therefore requires anti-aliasing filters
for best performance. However, because the human ear is not
sensitive to frequencies beyond about 20 kHz, the anti-aliasing
band stop can be set to 20 kHz below the sampling rate. For
example, in the case of an 85 kHz sampling rate, the band stop of
the anti-aliasing filter can be set to 65 kHz corresponding to (85
kHz-20 kHz). While this results in frequencies above 1/2 of the
sampling rate and below the stop band being aliased, corresponding
to 85 kHz/2 (or 42.5 kHz) to 65 kHz, these frequencies will not be
audible to the human ear and will not affect perceptible
performance. The higher anti-aliasing stop band is advantageous
because it allows the associated pass band of the filter to be
higher and thus have much lower group delay in the audible
range.
[0069] The audio processing for active noise reduction is performed
in real time by a digital signal processor, such as shown in the
system architecture block diagram illustrated in FIG. 6. However,
the filter adaptation described in detail with respect to FIGS. 4,
5, and 7A-7B, for example, does not need to be performed in real
time. Filter adaptation may be performed when the system
performance has changed due to a change in operating conditions,
such as altitude, fit, or other possible time varying parameters
including the ambient noise characteristics. Alternatively, filter
adaptation may be continuously performed to detect changes in
operating conditions by comparing calculated filter coefficients
with current (or preceding) filter coefficients. The new filter
coefficients may be used in response to detecting that operating
conditions have changed significantly. As previously described,
filter coefficients may be temporarily stored in persistent memory
for subsequent recall to reduce time associated with adaptation. Of
course, previously stored filter coefficients may not be
particularly suited for current operating conditions or fit.
[0070] FIG. 8 is a block diagram illustrating integration and
configurability details provided by a linked device or other user
interface for an adaptive ANR system or method according to various
embodiments of the present disclosure. As described in greater
detail below, personal preferences can be set using the enhanced
capability of a linked device, such as a smart phone. Bass and
treble levels of the intercom and auxiliary inputs can be adjusted
independently and separate intercom priority options can be set for
Bluetooth and wired input. The voice clarity option boosts
frequencies common to human speech without impacting the quality of
music from auxiliary devices.
[0071] As shown in FIG. 8, system 800 includes an input selector
module 810, an output selector module 820, and a DSP block
processing module 830 in communication with a controller 840, which
also communicates with Bluetooth (BT) data port 852 and Selector
Switch Input port 854. Input selector 810 communicates with wired
input ports including a boom microphone port 842, a communications
(Comm) input port 844, and an auxiliary (Aux) input port 846.
Output selector module 820 communicates with an auxiliary (Aux)
output port 860 and a Bluetooth (BT) audio output port 862. DSP
module 830 communicates with ports 842, 844, and 846 in addition to
a first BT audio input port 848 and a second audio input port 850,
which is configured for AD2P stereo input in the representative
embodiment illustrated.
[0072] In the representative embodiment of FIG. 8, the routing of
either the boom microphone signal/port 842, or the comm input port
844 is directed to the appropriate output port 860, 862 by output
selector 820 and may be specified manually by the user or
determined automatically by the system via controller 840. The
output selector 820 directs output to the wired auxiliary output
port 860 or to the wireless Bluetooth (BT) audio output port 862.
This allows an app running on a connected portable device (such as
a smart phone or tablet, for example) to operate as the user
interface to the ANR headset to adjust personalization settings
and/or headset performance. Voice commands processed by a linked
portable device can be communicated to the controller 840 of the
headset via the BT data port 852. Similarly, voice commands
captured by the boom microphone applied to port 842 can be sent to
a linked device for processing via output ports 860 or 862. The
boom microphone signal on port 842 may be manually or automatically
routed to the desired output depending on how the linked device is
coupled to the headset (wired, wireless, analog, or digital). For
example, the controller may automatically connect (route) the boom
microphone input port 842 via input selector 810 and output
selector 820 to a coupled cell phone in response to detecting a
phone call or dialing command as determined by controller 840. For
a cell phone linked by the Bluetooth modules 848 and 852, the
controller module 840 would connect the boom microphone port 842 to
the BT audio output port 862, whereas for a cell phone linked by
the auxiliary input port 846, the controller module 840 would
connect (route) the boom microphone port 842 to the auxiliary
output port 860 via controls or commands communicated to input
selector 810 and output selector 820, respectively. A connected
device may also communicate personalization commands to controller
840 to control headset features such as personal preference for
tone or performance of the noise reduction system (update rate,
saved personalization settings, etc.).
[0073] FIGS. 9-19 are graphs illustrating improved ANR performance
for an adaptive ANR system or method according to embodiments of
the present disclosure.
[0074] FIGS. 9 and 10 are graphs illustrating noise attenuation
performance of representative embodiments according to the present
disclosure for first and second noise inputs, respectively. Lines
910, 1010 represent passive attenuation, lines 920, 1020 represent
closed loop attenuation without feedforward, and lines 930, 1030
represent noise attenuation performance with both feedforward and
closed loop feedback.
[0075] FIGS. 11 and 12 illustrate amplitude and phase response,
respectively, as a function of frequency for a measured response of
the driver to error microphone transfer function on a user 1110,
1210 and realized adaptive correction filter H.sub.C 1210,
1220.
[0076] FIGS. 13 and 14 illustrate amplitude and phase response,
respectively, of T.sub.DM*H.sub.C as a function of the target open
loop response for closed loop noise reduction.
[0077] FIGS. 15 and 16 illustrate amplitude and phase response,
respectively, of T.sub.DM*H.sub.C as a function of the target
closed loop response for closed loop noise reduction.
[0078] FIGS. 17 and 18 illustrate a representative measured
attenuation transfer function 1710, 1810 (error mic noise/ambient
noise) and calculated/realized T.sub.ff 1720, 1820 for adaptive
feedforward (note that T.sub.ff is plotted as -T.sub.ff since
cancelation is the goal). It would not be possible to achieve this
level of phase matching without use of low latency components and
processing strategies according to embodiments of the present
disclosure.
[0079] FIG. 19 illustrates measured attenuation before and after
feedforward and the realized response of the feedforward transfer
function Tff.
[0080] As can be seen from the summary and detailed description and
review and analysis of the figures, embodiments of the present
disclosure may provide several advantages. For example, the
adaptive ANR embodiments according to the disclosure are believed
to provide the world's quietest aviation headset, and the only one
that actively conforms to users and the cockpit environment
creating custom noise cancellation and a uniquely personal ANR
experience based on measurement of transfer functions and
determination of adaptive filter coefficients to compensate for
them. The personalized experience is provided by acoustically
measuring and actively conforming to the user's ears, environment,
and preferences using acoustic response mapping to adaptively
adjust various system parameters. This technology uses sound waves
and advanced signal processing to measure a user's unique auditory
landscape adapting the audio response to the user's ears' size and
shape for maximum noise attenuation, voice clarity, and music
fidelity.
[0081] Various embodiments include streaming quiet ANR to adapt to
the environment with one or more ambient microphones to
continuously sample ambient noise before it penetrates the ear cup
of the headset. An internal error sensing microphone placed near
the ear canal monitors ANR performance. The microphones feed
information to the CPU, a powerful digital signal processor that
analyzes a stream of both the external ambient noise and internal
residual noise at a rate of one million times a second, for
example, and seemingly instantaneously creates precise ANR
responses customized to a dynamic sound environment. The result is
a dramatic extension in the amount, consistency, and frequency
range of noise cancellation regardless of the environment, fit, and
user, allowing important communication to come through with amazing
clarity and producing music with outstanding fidelity.
[0082] In addition to various personalization features provided by
a coupled mobile device such as a smart phone or tablet,
embodiments according to the present disclosure leverage the latest
technological advances across multiple fields. Rugged cables
constructed of silver coated copper alloy wrapped around a Kevlar
core deliver extraordinary flexibility, strength, and audio
quality. An aviation-friendly CPU provides powerful digital audio
processing and convenient access to key controls. Upgradeable
firmware provides unlimited potential for new software
innovations.
[0083] While exemplary embodiments are described above, it is not
intended that these embodiments describe all possible forms of the
invention. Rather, the words used in the specification are words of
description rather than limitation, and it is understood that
various changes may be made without departing from the spirit and
scope of the invention. Additionally, the features of various
implementing embodiments may be combined to form further
embodiments of the invention.
* * * * *